ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

OBJECTIVE To study the protective effect and potential mechanism of chikusetsu saponin Ⅳ a （chsⅣ） on renal function in diabetic nephropathy （DN） model rats. METHODS DN rat model was established by high-fat diet combined with streptozotocin injection. Thirty-six model rats were randomly divided into model group （i.g. administration of normal saline， high-fat diet）， chsⅣ low-dose and high-dose groups （i.g. administration of 90， 180 mg/kg chsⅣ， high-fat diet）， with 12 rats in each group. Additionally， 10 normal rats were set as the control group （i.g. administration of normal saline， regular diet）. From the 5th to the 12th week after streptozotocin injection， they were given intragastric administration of relevant drug or normal saline， once a day. After the last medication， the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine and urine protein as well as the levels of reduced glutathione （GSH）， superoxide dismutase （SOD） and malondialdehyde （MDA） in renal tissues were measured. Additionally， the insulin resistance index was calculated. Hematoxylin-eosin， periodic acid-Schiff， and Masson staining techniques were employed to examine the histopathological alterations in the renal tissue. The expressions of Notch signaling pathway-related proteins in renal tissue were detected by immunohistochemical staining and Western blot methods. RESULTS Compared with model group， the histomorphological of renal tissues in the chsⅣ low- and high-dose groups were significantly improved， with significant decreases in renal histological scores， mesangial expansion index， and glomerulosclerosis scores （ P ＜0.05）； the levels of fasting blood glucose， fasting insulin， blood urea nitrogen， serum creatinine， urine protein and homeostasis model assessment for insulin resistance， as well as MDA content， the expression levels of Notch1， Notch intracellular domain， hairy and enhancer of Split 1 and Delta-like protein 1 in renal tissue were all significantly decreased （ P ＜0.05）. The levels of GSH and SOD in renal tissue were significantly elevated （ P ＜0.05）. Moreover， the improvement in these indicators was significantly more pronounced in the chsⅣ high-dose group compared to the chsⅣ low-dose group （ P ＜0.05）. CONCLUSIONS ChsⅣ can ameliorate renal pathological damage and functional impairment in DN rats. Its underlying mechanisms include restoration of glucose homeostasis and insulin sensitivity， attenuation of renal oxidative stress， and suppression of aberrant Notch signaling pathway activation.

To analyze the clinical and genetic features of oculopharyngodistal myopathy (OPDM) patients and compare the phenotypic differences among various causative genes.

ObjectiveTo investigate the association between single and combined exposure to arsenic （As）， mercury （Hg）， and cadmium （Cd） in urine and hearing loss in adults. MethodsA total of 400 adult patients were recruited for the study， comprising 200 participants in the normal hearing group and 200 in the hearing loss group. General demographic information of the study subjects was collected by a self-administered questionnaire， morning urine samples were tested for As， Hg， and Cd concentrations， and hearing status was assessed by Pure Tone Audiometry. A binary Logistic regression model was used to explore the association between the concentrations of the three metals in urine and hearing loss， and a Bayesian kernel-machine regression （BKMR） model was used to further explore the association between the concentrations of the three metal mixtures and hearing loss. ResultsAfter correction for urinary creatinine， As， Hg， and Cd concentrations were higher in the hearing loss group than those in the normal hearing group （P<0.05）. Binary Logistic regression indicated that concentrations of As， Hg， and Cd were positively associated with hearing loss， and the risk of hearing loss was significantly higher in the second quartile of Cd concentration compared to the first quartile （OR=2.000， 95%CI： 1.009-3.964）. BKMR modeling analysis showed that the combined exposure levels of As， Hg， and Cd significantly increased the risk of hearing loss， with Cd being the most important contributor （posterior inclusion probability=0.412）， and that there were potential interactions between As and Cd， and Cd and Hg. ConclusionCombined exposure to As， Hg， and Cd in urine is significantly associated with adult hearing loss， with Cd being the primary contributor in the exposure combination. The interactions between As and Cd， as well as Cd and Hg， may have adverse effects on hearing loss.

β‑arrestin serves as a core functional effector governing signal transduction of G protein-coupled receptors (GPCRs), exerting dual roles as a signal terminator and molecular scaffold. However, the molecular mechanism underlying how β-arrestin responds to diverse GPCRs and interacts with hundreds of effector proteins to mediate a broad spectrum of physiological functions remains poorly understood. A landmark original study recently published in Nature overturned the conventional view of β‑arrestin as a static scaffold protein. Endogenously expressed β‑arrestin undergoes liquid-liquid phase separation (LLPS) to form highly dynamic biomolecular condensates, which orchestrate compartmentalized assembly and fine-tuning of GPCR signaling complexes. This work establishes a novel paradigm centered on β‑arrestin condensates for GPCR signal regulation and reshapes the molecular framework of hierarchically organized intracellular signaling networks.

Objective To investigate the effects of plateau hypoxia on the growth and tumor microenvironment of colorectal carcinoma in vivo.Methods A total of 16 male BALB/C mice(6 weeks old,weight 18-20 g)were randomly divided into plateau hypoxic group and plain normoxic group,with 8 mice in each group,while 14 male C57BL/6 mice were grouped in same way,with 7 mice in each group.The mice in the plateau hypoxic group were housed in a low-pressure oxygen(10%)chamber to simulate an altitude of approximately 5 600 m,while the mice of the other group was maintained in SPF-grade normal atmospheric conditions(21%oxygen,at an altitude of about 300 m).Colorectal tumor MC38 cells and colon adenocarcinoma CT26 cells were subcutaneously implanted into C57BL/6 mice and BALB/C mice,respectively to construct subcutaneous tumor-bearing mouse models.Then the tumor size and weight were measured in 4 groups of mice.After the tumor tissues,spleen and blood samples were collected in the C57BL/6 mice.Flow cytometry was used to determine the percentages of macrophages,T lymphocytes,IFN-γ+T lymphocytes,and myeloid-derived suppressor cells(MDSC).The differences in these immune cells were compared between the cells from the plateau hypoxic group and those from the plain normoxic group.Results The weight of subcutaneous tumor mass was significantly inhibited in both C57BL/6 and BALB/C mice from the plateau hypoxic group than those from the 2 plain normoxic groups(0.17 vs 0.09 g,1.38 vs 0.51 g,P<0.01).When compared with the immune cells from the tumor mass of the plain normoxic C57BL/6 mice,the percentage of M2-type macrophages was reduced in the tumor tissue from the plateau hypoxic mice(22.13%vs 15.90%,P<0.05),so was that of MDSC(2.06%vs 1.05%,P<0.01),particularly in the monocytic(M)-MDSC subgroup(60.97%vs 41.13%,P<0.01).While,no significant change was observed in the proportion of the polymorphonuclear(PMN)-MDSC subgroup(10.97%vs 9.70%,P>0.05).Additionally,the percentage of CD4+T cells was significantly reduced(48.70%vs 41.93%,P<0.05),whereas that of CD8+T cells was obviously increased(41.25%vs 51.18%,P<0.05),along with a notable rise in the proportions of IFN-γ+T,IFN-γ+CD4+T and IFN-γ+CD8+T cells(28.58%vs 59.65%,23.33%vs 53.65%,36.9%vs 66.48%,P<0.01).However,between the peripheral blood samples of the 2 groups of C57BL/6 mice,the proportions of M1-type macrophages and CD4+T cells were reduced(84.98%vs 78.43%,5.86%vs 4.01%,P<0.01),and those of MDSC and PMN-MDC were increased(4.47%vs 16.43%,36.56%vs 62.97%,P<0.01).In the spleen tissues,notable decreases were observed in the proportions of CD8+T cells and IFN-γ+CD8+T cells between the 2 groups(33.05%vs 27.68%,5.13%vs 1.58%,P<0.01).Conclusion Plateau hypoxia improves the immune response within the tumor microenvironment,and inhibits subcutaneous tumor growth of colorectal cancer,but suppresses systemic immune response.

Objective To explore the association between single nucleotide polymorphism(SNP)of Rab37 gene and the age at menarche(AAM).Methods A case-control study design was used to conduct an epidemiologic survey on 2 060 women in a community in Jurong City,Jiangsu Province,and their venous blood samples were collected.ASA chip was used to explore the Rab37 gene genotyping of blood sample DNA to obtain the genotyping results for Rab37 SNPs rs62084865,rs10512597,rs35489971,rs1037170,rs6501732,rs77822106,and rs3178300.Based on menarche time of＜16 years old or≥16 years old,the participants were divided into 2 groups.Linear and logistic regression analyses were used to explore the association between the SNP of Rab37 gene and the age at menarche based on dominant,recessive and allelic models.Results Among the 2 060 healthy women,944 women had normal menstrual periods,while 1 116 women experienced delayed menarche.Linear regression analysis showed that the gene polymorphism of rs3178300 was negatively correlated with the age at menarche in females[recessive model:CC/CT+TT,β=-0.915,95%CI(-1.692,-0.137),P=0.021;allelic model:T/C,β=-0.221,95%CI(-0.410,-0.032),P=0.022].Logistic regression analysis indicated that the gene polymorphism of rs3178300 was significantly associated with the risk of delayed menarche in females[recessive model:CC/CT+TT,OR=0.295,95%CI(0.116,0.751),P=0.010;allelic model:T/C,OR=0.796,95%CI(0.652,0.972),P=0.025].The remaining 6 SNPs showed no significant association with age at menarche.Conclusion The rs3178300 polymorphism of Rab37 gene is significantly associated with delayed menarche in Chinese women.

Iodine speciations in aquatic environments are affected by dissolved oxygen,redox potential,microbial activity,organic matter decomposition,light reaction,etc.Accurate quantification of iodine speciation can not only help to understand the geochemical cycle of iodine,but also help to trace and study environmental processes.Based on the combination of ion chromatography(IC)and inductively coupled plasma mass spectrometry(ICP-MS),a rapid and sensitive method was established for determining the speciations of iodine in environmental water samples including seawater,river water,lake water,rainwater,groundwater,etc.The results presented here showed that IO3?and I?in seawater were quickly separated and measured within 120 s when using guard column AG22 and 8 mmol/L(NH4)2CO3 as the mobile phase.While for lake water,river water and precipitation samples with high soluble organically bond iodine(SOI),an AS22 separation column(250 mm×4 mm)connected with a guard column and using 50 mmol/L(NH4)2CO3 as mobile phase could effectively separate unknown SOI from IO3? to achieve accurate quantification of IO3?.For accurate correction of iodine measurement signal fluctuations,133Cs was directly added to the(NH4)2CO3 mobile phase as an internal standard.The SOI content was calculated by the total iodine concentrations minus the sum of IO3?and I?.The precision of the established iodine speciation analytical method was better than 3.5%,and the standard addition experiment showed that the analytical method was accurate.When the injection volume was 25 μL,the detection limits were 0.011?0.025 μg/L for IO3? and 0.023?0.031 μg/L for I?,respectively.The method was successfully used to analyze IO3?,SOI and I? in environmental water samples,such as seawater,river water,rainwater and groundwater.

A deep learning-based method for recognizing the minutiae in fingerprint,as well as a Python programming-based evaluation system for quantifying the evidence value of fingerprint was proposed.Firstly,latent fingerprints,which were developed using a series of fluorescent nanomaterials synthesized by chemical methods,were used as unknown fingerprint(UKFP),while ink impressed fingerprints were used as known fingerprint(KFP).Then,the bifurcations and terminations in minutiae were recognized using the improved YOLOv8 deep learning model.After that,the similarity index(Sim.)of UKFP vs KFP were calculated by analyzing the angle similarity factor(α)and the curve similarity factor(β)between UKFP and KFP,meanwhile,the sensitivity index(Sen.)were calculated by analyzing the fineness factor(γ)between UKFP and KFP.The evidence value(EV)of fingerprint was thus obtained by the combination of Sim.and Sen..The calculation formulas for above evaluation factors(i.e.α,β and γ),evaluation indexes(i.e.Sim.and Sen.),and EV were also put forward.Finally,the evaluation system for quantifying the evidence value of fingerprint was established,the feasibility and reliability of this system were verified,and the external factors that impacted on Sim.,Sen.,and EV were investigated in detail.The Python-based evaluation system for quantifying the evidence value of fingerprint could achieve the goals objectively,comprehensively,accurately and efficiently,exhibiting easy operability,high efficiency,responsiveness and reliability.This research was expected to provide beneficial references for quantitatively evaluating and thoroughly developing the evidence value.